Open AccessA field guide to cultivating computational biology
Author(s) -
Gregory Way,
Casey S. Greene,
Piero Carninci,
Benilton Carvalho,
Myung Hoon,
Stacey D. Finley,
Sara J.C. Gosline,
KimAnh Lê Cao,
Jerry S. H. Lee,
Luigi Marchionni,
Nicolas Robine,
Suzanne Sindi,
Fabian J. Theis,
Pengyi Yang,
Anne E. Carpenter,
Elana J. Fertig
Publication year - 2021
Publication title -
plos biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.127
H-Index - 271
eISSN - 1545-7885
pISSN - 1544-9173
DOI - 10.1371/journal.pbio.3001419
Subject(s) - biology , field (mathematics) , multidisciplinary approach , engineering ethics , computational model , data science , order (exchange) , management science , computer science , artificial intelligence , sociology , social science , engineering , mathematics , finance , pure mathematics , economics
Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.